Seminars – From Systems Biology to Systems Ecology

EVENT : C3BI Seminars

From Systems Biology to Systems Ecology: A computational journey from Genes to ecosystem


Main speaker : Damien Eveillard, from LINA UMR 6241 CNRS, EMN, University of Nantes, Date : 17/11/2016 at 02:00 pm Location : Retrovirus room – LWOFF (22), Institut Pasteur, Paris


From systems biology to systems ecology: a computational journey from genes to ecosystems

Recent progresses in metagenomics have promoted a change of paradigm to investigate microbial ecosystems. These ecosystems are today analyzed by emphasizing either their gene content or «  who is there and who is not » from a taxonomical viewpoint. However, understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. Such a task must be achieved by dedicated computational approaches or modelings, as inspired from Systems Biology.  Nevertheless, direct application of standard cellular systems biology approaches is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete.

Within this seminar, we will illustrate how systems biology approaches must be adapted to overcome these points in different manners. First, we will present a network analysis that focus on the global ocean.  Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve understanding of a biological process such as the carbon export. Additionally, we will show that the abundances of just a few bacterial and viral genes predict most of the global ocean carbon export’s variability. Second, we will describe how to integrate heterogeneous omics knowledge. Such an integration will emphasize putative functional units at the community level. Finally, we will illustrate a quantitative modeling that predicts microbial community structure across observed physicochemical data, from a putative network and partial quantitative knowledge. This modeling shows that, despite distinct quantitative environmental perturbations, the constraints on the community structure could remain stable.

Due to security policy in Institut Pasteur, please register before if you plan to come to this meeting